HERNANDEZ RUIZ, JOSELIN

I am a translational immunology researcher with over 10 years of experience integrating clinical data, genomics, and computational approaches to understand complex immune-mediated diseases.

My work is driven by a central question: how can we move from fragmented biological signals to actionable clinical insight? To address this, I combine mechanistic immunology with bioinformatics, focusing on biomarker discovery, disease stratification, and predictive modeling.

Throughout my career, I have led and contributed to multidisciplinary projects spanning liver disease, pediatric inflammatory conditions, and metabolic disorders, including Kawasaki Disease, biliary atresia, and pre-eclampsia. My recent work emphasizes the integration of RNA-seq, clinical data, and probabilistic modeling to characterize disease trajectories and uncover underlying regulatory mechanisms.

In Kawasaki Disease, I have applied RNA-seq analysis to differentiate it from MIS-C, identifying distinct immune signatures. In biliary atresia and pre-eclampsia, I work on large-scale data integration, combining genomics and clinical variables using trajectory networks and Bayesian approaches (e.g., bnlearn) to model disease progression and outcomes.

Earlier in my career, I led translational research programs in Mexico, where I served as corresponding author on multiple publications and managed federally funded projects. I also developed applied tools such as HepaScan (for liver fibrosis imaging analysis) and HEPCA, a clinical instrument to assess alcohol consumption patterns, reflecting my interest in bridging research and real-world application.

Currently, I am a Research Associate at the University of Utah (3i–UCGD Bioinformatics Core), where I collaborate on NIH-funded projects involving noncoding genetic variation and complex disease modeling, as well as global health initiatives using genomics-based epidemiological surveillance.

My approach is inherently interdisciplinary: I work across molecular biology, clinical datasets, and computational modeling, with the goal of building integrative frameworks that improve diagnosis, prognosis, and ultimately patient care.

I am particularly interested in advancing toward independent research that leverages AI, probabilistic modeling, and multi-omics integration to better understand immune-driven diseases in complex clinical settings.